Pollutant Emissions Research Articles

Establishment of circular economy by utilising textile industry waste as an adsorbent for textile dye removal

This study explored the use of waste from the textile industry (silkworm byproducts) as a promising raw feedstock for the production of carbon-based adsorbents (biochar). The silk excreta biochar generated at 600 and 700 °C (referred to as SEB-600 and SEB-700, respectively) were evaluated in terms of their efficacy in adsorbing cationic (methylene blue) and anionic (Congo red) textile dyes. Although the functional groups on the surfaces of SEB-600 and SEB-700 were not significantly different, the specific surface area of SEB-700 was greater than that of SEB-600. The dye adsorption capacity of SEB-700 was higher than that of SEB-600. The adsorption of methylene blue and Congo red on SEB-700 followed Freundlich isotherms (R2 ≥ 0.963) and pseudo-second-order kinetics (R2 = 0.999), indicating chemisorption with multilayer characteristics. The mechanism for the adsorption of methylene blue on SEB-700 may involve interactions with the negatively charged functional groups on the surface and the mesopores of SEB-700. For the adsorption of Congo red, the mesopores in the biochar and the electrostatic interaction between biochar (positively charged because of the dye solution pH < pHzpc) and the anionic dye could affect adsorption. The maximum adsorption capacities of SEB-700 for methylene blue and Congo red were determined to be 168.23 and 185.32 mg g−1, respectively. Utilising the waste generated from the textile industry to remove pollutants will build a sustainable loop in the industry by minimising waste generation and pollutant emissions.

Integration of the wind and solar power for the dynamic economic emission dispatch with the charging and discharging of plug-in electric vehicles

Wind and solar power are incorporated into the dynamic economic emission dispatch with the plug-in electric vehicles (DEED-PEV) in this paper, seeking to reduce the generation cost and pollutant emission significantly. A Laplacian non-dominated sorting genetic algorithm-II (LNSGA-II) and a constraint handling method (CHM) are proposed for the DEED-PEV. The LNSGA-II applies the Laplace distribution to both the crossover and mutation. The Laplace-based crossover makes each individual carry out unidirectional search towards its partner and enhances the information exchange between each pair of individuals. The Laplace-based mutation makes each individual carry out bi-directional search surrounding itself and adjust the searching range adaptively. Therefore, the LNSGA-II is able to explore and exploit the decision space of the DEED-PEV sufficiently, contributing to the reductions of the generation cost and pollutant emission in the objective space. For the variables of every individual, the CHM limits them within the feasible operating zones. The CHM also limits them within the dynamic boundaries. It further adjusts them according to the power balances. The power generation constraints and up/down ramp rate constraints can be always satisfied while the elimination of the total violation of the other constraints can be expedited. Therefore, the CHM can transform infeasible individuals to feasible ones rapidly. Four strategies are investigated for six PEV charging/discharging scenarios. The first three strategies consider no more than one kind of renewable energy generation while the fourth strategy involves both the wind power and solar power. Experimental results suggest that the fourth strategy is more economical and environment-friendly than the other three strategies. Furthermore, the LNSGA-II outperforms the other three competitor algorithms for six DEED-PEV problems in the light of hypervolume, coverage rate and spacing.

Insights Into the Influence of Anthropogenic Emissions on the Formation of Secondary Organic Aerosols Based on Online Measurements

AbstractTo investigate the combined impacts of anthropogenic and biogenic emissions on the formation of secondary organic aerosols (SOA), SOA molecular tracers, their corresponding volatile organic compound precursors, and other air pollutants were measured online during the winter and summer seasons of 2022 in an industrial city, Zibo, China. The results indicate that the average concentrations of SOA tracers were 16.1 ± 9.8 ng m−3 in winter and 99.4 ± 57.2 ng m−3 in summer. During winter, anthropogenic SOA (ASOA, the sum of SOA derived from naphthalene and mono‐aromatic volatile organic compounds) dominated, whereas isoprene SOA (SOAI) prevailed in summer. Correlation analysis between SO42− and both SOAI and high‐order monoterpene SOA tracers (SOAM‐H) (R = 0.46–0.72, p &lt; 0.001) revealed that higher aerosol acidity facilitated the formation of SOAI and SOAM‐H, with SO2 emissions playing a significant role in leading to higher acidity. Most biogenic SOA (BSOA) tracers exhibited a significant positive correlation with NO3−, particularly in winter, implying the remarkable influence of NOx emissions on BSOA formation. The levels of BSOA tracers increased with NH3, indicating that NH3 can enhance the formation of BSOA. In summer, SOA formation correlated with Ox (Ox = O3 + NO2), indicating the substantial impact of atmospheric oxidizing capacity on SOA formation. During winter, aerosol liquid water content (ALWC) correlated well with SOAI tracers (i.e., 3‐hydroxyglutaric acid (3‐HGA) and 3‐hydroxy‐4,4‐dimethylglutaric acid (3‐HDMGA)), and 2,3‐dihydroxy‐4‐oxopentanoic acid (DHOPA) (R &gt; 0.5, p &lt; 0.001), indicating the important contribution of aqueous‐phase formation of SOA. These findings underscore the significant role of anthropogenic pollutant emissions in the formation of ASOA and BSOA in urban environments.

Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools

Monitoring air quality in livestock farming facilities is crucial for ensuring the health and well-being of both animals and workers. As livestock farming can contribute to the emission of various gaseous and particulate pollutants, there is a pressing need for advanced air quality monitoring systems to manage and mitigate these emissions effectively. This study introduces a multi-sensor air quality monitoring system designed specifically for livestock farming environments. Utilizing open-source tools and low-cost sensors, the system can measure multiple air quality parameters simultaneously. The system architecture is based on SOLID principles to ensure robustness, scalability, and ease of maintenance. Understanding a trend of evolution of air quality monitoring from single-parameter measurements to a more holistic approach through the integration of multiple sensors, a multi-sensor platform is proposed in this work. This shift towards multi-sensor systems is driven by the recognition that a comprehensive understanding of air quality requires consideration of diverse pollutants and environmental factors. The aim of this study is to construct a multi-sensor air quality monitoring system with the use of open-source tools and low-cost sensors as a tool for Precision Livestock Farming (PLF). Analysis of the data collected by the multi-sensor device reveals some insights into the environmental conditions in the monitored barn. Time-series and correlation analyses revealed significant interactions between key environmental parameters, such as strong positive correlations between ammonia and hydrogen sulfide, and between total volatile organic compounds and carbon dioxide. These relationships highlight the critical impact of these odorants on air quality, emphasizing the need for effective barn environmental controls to manage these factors.

Regional Differences in Effects of Foreign Trade and FDI on Air Pollutant Emissions in China

Regional Differences in Effects of Foreign Trade and FDI on Air Pollutant Emissions in China

Impact of green infrastructure on PM10 in port-adjacent residential complexes: A finite volume method-based computational fluid dynamics study

This study examines the effects of PM10 reduction by introducing green infrastructure (GI) in residential areas adjacent to ports, where significant pollutant emissions from ships are prevalent. Using finite volume method (FVM)-based computational fluid dynamics (CFD) simulations, we evaluated 30 scenarios based on various GI types and spacings and validated these simulations using observational data. The assessed GI types included trees and shrubs (hedges). Planting configurations were categorized into single (T for trees, H for hedges) and mixed (TH for both trees and hedges) plantings, with one or two rows and spacings of trees from 6 m to 14 m at 2 m intervals. We also considered both aerodynamic and depositional effects as mechanisms for PM10 reduction by GI. Our results revealed the following: 1) Plant spacing significantly influenced PM10 reduction, with both excessively narrow and wide spacings being suboptimal. (2) Trees proved to be more effective, whereas combining them with shrubs offers limited advantages. 3) Among the shrubs, the adsorption effect was more influential on PM10 reduction than the aerodynamic effects. These insights are not limited to port regions but also offer foundational knowledge for enhancing urban air quality, setting the groundwork for subsequent studies.

Unveiling BTX dynamics, source identification, and health implications during COVID-19 lockdown

The COVID-19 pandemic of 2020, marked by stringent lockdowns and reduced human activity, resulted in a significant decrease in air pollutant emissions. This study investigates the impact of these altered atmospheric conditions on human health by focusing on Volatile Organic Compounds (VOCs) such as benzene, toluene, and meta-xylene (BTX), comparing data from before, during, and after the pandemic lockdowns. The objectives were to assess changes in Total VOC (TVOC) concentrations and to evaluate the associated health risks, particularly Lifetime Cancer Risk (LCR) from benzene exposure. Analysis of the data revealed a notable reduction in TVOCs during the 2020 lockdown, with average concentrations of 12.15 ± 20.49 µg/m3 in 2019, 8.08 ± 5.50 µg/m3 in 2020, and 5.12 ± 7.56 µg/m3 in 2021. LCR values also fluctuated, with averages of 1.12 × 10−5, 1.23 × 10−5, and 6.91 × 10−6 or pre-pandemic, during-pandemic, and post-pandemic periods, respectively. The findings highlight the potential effectiveness of lockdowns in reducing air pollution and underscore the need for continued, targeted environmental policies to improve public health.

Towards Green and Low-Carbon Transformation via Optimized Polygeneration System: A Case Study of the Iron and Steel Industry

Polygeneration systems have significant potential for energy conservation and emission reduction and can effectively promote green and low-carbon development in energy-intensive industries, such as the iron and steel industry. However, its application faces the difficulty in technology selection under multiple objectives simultaneously, which is to determine the technology portfolio to achieve the synergy of energy conservation goals and air pollutant emission reduction goals, as well as ensure the economic benefits of the enterprises. This study investigated a case polygeneration system where the iron and steel plant are the core with four polygeneration paths and twenty polygeneration technologies. A multi-objective optimization model is developed to select the optimal technology combination of each polygeneration path under energy conservation, emission reduction, and cost control objectives, which is solved by the non-dominated sorting genetic algorithm-II (NSGA-II). The optimal results can reach significant energy conservation and emission reduction effects while obtaining economic benefits. However, synergistic and conflicting relationships among the objectives exist in both scales of iron and steel plants. The final decision scheme can achieve the mitigations equivalent to 15.9–27.1% and 16.3–42.6% of the energy consumption and air pollutant emissions of the steel enterprises with annual production of 3 Mt/a and 9 Mt/a, respectively. There are thirteen and twelve technologies that are selected as the final decision scheme in the polygeneration system in these two case enterprises. These findings demonstrate the significant roles the polygeneration system plays and provide critical insights and methodology in the technical selection of the polygeneration system.

Spatiotemporal Characteristics and Influencing Factors of the Synergistic Effect of Pollution Reduction and Carbon Reduction in China

Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted "U"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.

Unveiling the green path: How urban openness reduces pollution and paves the way to sustainability

This study investigates the relationship between openness and pollutant emission intensity across 286 Chinese cities from 1990 to 2019, aiming to evaluate the potential environmental benefits of open economy strategies. The findings indicate that enhanced urban openness significantly lowers pollutant emission intensity. To ensure the robustness of our findings, we make an innovative attempt to employ high-speed rail connection and motorway density as instrumental variables to address potential endogeneity issues, corroborating the reliability of the results through various robustness tests. Moreover, we also find the heterogeneous effects of urban openness on pollution emissions, highlighting the moderating influences of trade complexity, urbanization level, and environmental regulatory intensity. Lastly, the study elucidates the mechanisms through which urban openness diminishes pollution emissions, namely fostering green innovation capacity and enhancing public environmental awareness. This research makes theoretical contributions on understanding the nexus between open economies and environmental protection while offering practical insights to inform governmental environmental policy formulation.

Heterogeneous evolution and driving forces of multiple hazardous air pollutants and GHGs emissions from China's primary aluminum industry

The booming of China's primary aluminum industry (PAI) brought substantial emissions of hazardous air pollutants (HAPs) and greenhouse gases (GHGs). By using life cycle assessment and bottom-up method, a comprehensive emission inventory for multiple typical HAPs and GHGs from China's PAI during 1990–2021 was developed and explored for the first time. Our results show that spatial-temporal emissions trends of HAPs and GHGs from PAI in China diverse significantly. The conventional atmospheric pollutants (including SO2, NOx and particulate matter (PM)), fluoride and per fluorinated compound (PFCs) had been effectively suppressed since 2007 due to the implementation of various environmental policies; while, emissions of CO, VOCs, CH4, heavy metals and CO2 had increased at different rates unexpectedly. From the spatial distribution perspective, Henan, Shanxi, Guizhou, Guangxi and Shandong dominated the emissions of PAI in China, but with consumption expansion and environmental constrains, PAI plants start to expand to northwest and southwest areas where are richer in sufficient and cheaper power resources, thus bring significant emission increasing there, particular for conventional atmospheric pollutants in northwest and CO and VOCs in southwest China. By underlying driving forces of PAI emissions, results show that end-of-pipe control measures at various stages have played different roles to reduce emissions of the concerned species at each period, but its reduction effect diminished gradually. Future reduction should seek underlying changes in production technology and energy system. Under constrains of environmental regulation and resource endowment, promoting circular economic development for PAI would be a key strategy to reduce HAPs and GHGs emissions simultaneously in PAI.

Government relocation and air pollution: Evidence from China

In the pursuit of sustainable economic development, many cities have initiated the relocation of government offices as a strategy to optimize resource allocation. This study examines the environmental impacts of local government relocations in China between 1999 and 2016, with a focus on PM2.5 concentration data in the areas surrounding the relocation sites. Utilizing a difference-in-differences estimation approach, our findings indicate that (1) relocating local government offices significantly reduces pollution levels in nearby areas, with more pronounced effects closer to the relocation site; (2) environmental quality improvements intensify over time before stabilizing; (3) the relocation reform enhances the overall environmental quality of the entire city; and (4) government site relocations ultimately lead to regional environmental quality improvements by fostering the development of clean industries and reducing industrial pollution emissions. These results underscore the policy significance of green development principles and the spatial optimization of public resources.

Combustion characteristics on ammonia injection velocity and positions for ammonia co-firing with coal in a pilot-scale circulating fluidized bed combustor

Ammonia (NH3) co-firing with coal in thermal power plant offers a viable solution for reducing CO2 emissions. Optimizing the NH3 injection method is crucial to achieving comparable performance and pollutant emissions in NH3–coal co-firing compared to coal only combustion in a circulating fluidized bed combustion system. The impact of NH3 co-firing with coal on the injection velocity and location in related to the NH3 supply method was evaluated. Injection velocity was controlled by varying the number of ammonia supply ports and their heights (0.2 m and 1.8 m from the distributor). Injecting NH3 through one port at a high velocity of 2.4 m/s increases CO emissions while decreasing NO emissions due to the formation of a reducing environment. Conversely, utilizing two ports with low NH3 injection velocity of 1.2 m/s exhibited the opposite trend in CO and NO emissions, achieving the highest combustion efficiency without the formation of N-containing components. This injection velocity promotes better mixing of gases (air and NH3) and solids (bed materials and coal) without hindering coal combustion. Regarding greenhouse gases emissions, the part of CO2 emissions decreased by considering CO2 concentration and flue gas flow rate, while the part of N2O emissions significantly increased due to N-chemistry by > 5 times.

How sustainable are agricultural practices in European Union countries? A spherical fuzzy logic based evaluation

ABSTRACT Climate change and population growth have heightened the need for a comprehensive framework to analyse the environmental impacts of agricultural practices. While traditional agricultural activities have detrimental environmental effects such as soil degradation, water pollution, and greenhouse gas emissions, sustainable agriculture is an innovative approach to minimizing humanity’s significant problems, such as depletion of natural resources, climate change, and biodiversity loss. In this study, a model is developed to evaluate the agri-environmental performance of countries. This model evaluates and ranks countries using the spherical fuzzy analytical hierarchy process and grey relational analysis methods within the European Union’s agri-environmental indicators framework. This study is among the pioneering studies to utilise the spherical fuzzy logic approach for determining the relative importance of agri-environmental performance criteria. The findings reveal that crucial factors such as the irrigable utilised agricultural area, the sales of pesticides per utilised agricultural area, and the share of main livestock types in total livestock units are critical to agri-environmental performance. In addition, in the implementation phase of the study, the performances of the European Union member countries are evaluated using the proposed model. This constitutes another contribution of the research. The results of this study indicate that Finland, Lithuania, and Sweden are the frontrunners in agri-environmental performance, while Italy, the Netherlands, and Malta rank lower. The model developed in this study has far-reaching implications for developing targeted environmental protection policies and advancing sustainable agricultural practices on a global scale.

Study on rapid policy-based strategic environmental assessment-taking China's regional development policy of Zhejiang Pilot Free Trade Zone as an example

Strategic Environmental Assessment(SEA) is acknowledged to be an important decision support tool. SEA concerns potential environmental impacts of decisions made by policy, plan and programs. At present, policy-based SEA is still in the exploratory stage in China. The development of policy-based SEA is extremely slow due to institutional and technical difficulties. In practice, the time from policy proposals to policy implementation is relatively short. So the corresponding policy-based SEA should reflect the characteristics of rapidity, centre on the seriously negative impact that may be caused policy implementation, and provide early and initial warnings.A simple and rapid framework was designed for policy-based SEA in this study. The framework includes four parts, namely, policy analysis, eco-environmental impact identification, eco-environmental sensitivity assessment, policy recommendations. Following this framework, regional development policy of Zhejiang Pilot Free Trade Zone (FTZ) was assessed. Results reveal that: 1)seriously negative environment impacts may arise from petroleum refining and chemical industry, oil and gas storage and transportation, iron ore transportation, liquid bulk commodities transportation. 2) Central Daishan area, Shengsi archipelago, Taohua Island, Liuheng island in Zhejiang FTZ is relatively of high eco-sensitivity, thus the fore-mentioned activities should be environmentally friendly or restricted in these areas. 3)In the future, continuous efforts should be made to promote sealing and automation of petroleum refining, chemical industry. Green petrochemical manufacturing technology utilization is recommended to reduce pollution from the source. Further, accelerating the construction of transportation pipelines is suggested in order to reduce air pollutants emissions caused by vehicle transportation activities. Fishery stock enhancement and releasing is recommended to counteract negative impact on fishery caused by iron and liquid bulk commodity marine transportation.

Insight of effects of air quality and sustainable aviation fuel blend on energy saving and emission reduction in airport

Air quality in airport attracts a widespread attention due to the emission of GHGs and pollutants related with aircraft flight. Sustainable aviation fuel (SAF) has confirmed PM2.5 reduction due to free of aromatics and sulphur, and thus air quality improvement in airport is prospected by SAF blend. Two types of SAF were assessed the potential of energy saving and emission reduction by ZF850 jet engine. FT fuel is characterized with only paraffins without aromatics and cycloparaffins while HCHJ fuels is characterized with no aromatics. The descend of air quality and SAF blend were both investigated the effect on the engine performance and emission characteristic. The critical parameters were extracted from fuel compositions and air pollutants. Ambient air with a higher PM2.5 could lead to the rise of engine emission especially in UHC and PM2.5 despite at the low thrust setting and high thrust setting, and even couple with 3.2% rise in energy consumption and 1% reduction in combustion efficiency. CO, NO and NO2 in ambient air show less influence on engine performance and emission characteristic than PM2.5. Both types of SAF blend were observed significant reductions in PM2.5 and UHC. PM2.5 reduction obtained 37.9%—99.8% by FT blend and 0.64%-93.9% by HCHJ blend through the whole trust settings. There are almost 6.67% positive benefit in TSFC through the whole thrust setting by 7% FT blend. The effects of air quality and SAF blend on engine emission present significant changes on PM and UHC but the slight change on CO and NOx. By SAF blend, the energy saving and pollutant reduction obtained could be both benefit for air quality improvement in airport and further reduce engine emission as the feedback of less pollutants in ambient air.Graphical

A local-to-global emissions inventory of macroplastic pollution

Negotiations for a global treaty on plastic pollution1 will shape future policies on plastics production, use and waste management. Its parties will benefit from a high-resolution baseline of waste flows and plastic emission sources to enable identification of pollution hotspots and their causes2. Nationally aggregated waste management data can be distributed to smaller scales to identify generalized points of plastic accumulation and source phenomena3–11. However, it is challenging to use this type of spatial allocation to assess the conditions under which emissions take place12,13. Here we develop a global macroplastic pollution emissions inventory by combining conceptual modelling of emission mechanisms with measurable activity data. We define emissions as materials that have moved from the managed or mismanaged system (controlled or contained state) to the unmanaged system (uncontrolled or uncontained state—the environment). Using machine learning and probabilistic material flow analysis, we identify emission hotspots across 50,702 municipalities worldwide from five land-based plastic waste emission sources. We estimate global plastic waste emissions at 52.1 [48.3–56.3] million metric tonnes (Mt) per year, with approximately 57% wt. and 43% wt. open burned and unburned debris, respectively. Littering is the largest emission source in the Global North, whereas uncollected waste is the dominant emissions source across the Global South. We suggest that our findings can help inform treaty negotiations and develop national and sub-national waste management action plans and source inventories.

Analysis of PM2.5 Concentration Released from Forest Combustion in Liangshui National Natural Reserve, China

(1) Background: In recent years, forest fires have become increasingly frequent both domestically and internationally. The pollutants emitted from the burning of fuel have exerted considerable environmental stress. To investigate the influence of forest fires on the atmospheric environment, it is crucial to analyze the variations in PM2.5 emissions from various forest fuels under differing fire conditions. This assessment is essential for evaluating the effects on both the atmospheric environment and human health. (2) Methods: Indoor simulated combustion experiments were conducted on the branches, leaves, and bark of typical tree species in the Liangshui National Natural Reserve, including Pinus koraiensis (PK), Larix gmelinii (LG), Picea koraiensis (PAK), Betula platyphylla (BP), Fraxinus mandshurica (FM), and Populus davidiana (PD). The PM2.5 concentrations emitted by six tree species under various combustion states were measured and analyzed, reflecting the impact of moisture content on the emission of pollutants from fuel combustion, as indicated by the emission factors for pollutants. (3) Results: Under different fuel loading and moisture content conditions, the mass concentration values of PM2.5 emitted from the combustion of different organs of various tree species exhibit variability. (4) Conclusions: Among the various tree species, broad-leaved varieties release a greater quantity of PM2.5 compared to coniferous ones. A positive correlation exists between the moisture content of the fuel and the concentration of PM2.5; changes in moisture content notably influence PM2.5 levels. The emission of PM2.5 from fuel with varying loads increases exponentially. Utilizing the Response Surface Methodology (RSM) model for simulation, it was determined that both moisture content and fuel load exert a significant combined effect on the release of PM2.5 during combustion.

Energy, economic and environmental analysis of a photovoltaic-thermal integrated dual-source heat pump system under a system coefficient of performance − based switching strategy

The photovoltaic-thermal integrated dual-source heat pump system can offer performance improvement by addressing the limitations of a single heat pump system, which not only improves energy efficiency and system performance but also reduces pollutant emissions. However, the operational performance of the system is significantly affected by different switching strategies between two heat sources, which has not been given adequate attention from researchers. Therefore, this study introduced a system coefficient of performance − based switching strategy, which can alternate between air-source heat pump and solar water heat pump modes to make full use of air and solar energy, to optimize the operation of the photovoltaic-thermal integrated dual-source heat pump system and compare with the conventional water temperature of the heat storage tank − based switching strategy. A TRNSYS model of the system was developed and validated, and the simulated results demonstrated the better performance of system coefficient of performance − based switching strategy in energy, economic and environmental perspectives. The average photoelectric and photothermal conversion efficiency under system coefficient of performance − based switching strategy were higher than those under water temperature of the heat storage tank − based switching strategy by 1.1 % and 4.0 %, respectively, with average modified coefficient of performance of 7.43 and 6.55. Furthermore, the system not only achieved savings of 5.63 % in annual electrical cost and 5.33 % in yearly operational cost but also reduced standard coal by 19.25 kg and total pollutant emissions by 242.55 kg per year under system coefficient of performance − based switching strategy, compared to water temperature of the heat storage tank − based switching strategy.

IoT-ENHANCED SHALE OIL AND GAS GREEN DEVELOPMENT: STATUS AND FUTURE

Shale oil and gas, deemed as vital alternative resources to conventional oil and gas, have spurred significant interest in information-based exploration and development technologies within the industry in recent years [1]. China boasts extensive shale oil and gas reserves, with the International Energy Agency (EIA) estimating China's shale oil technology capable of extracting approximately 4.393 billion tonnes, ranking third globally. Additionally, China holds shale gas geological resources of about 134.4 trillion cubic meters, ranking first worldwide, showcasing immense development potential. Shale oil and gas, being unconventional resources, are distributed within the pore and fracture systems of organic-rich shale formations. Compared to conventional oil and gas, shale oil and gas exhibit weaker trap control and stronger distribution continuity, typically characterized by poor reservoir physical properties. Conventional extraction methods often struggle to yield industrial oil and gas flow from shale oil and gas resources, necessitating unconventional development technologies such as reservoir monitoring, directional wells, horizontal wells, and segmental fracturing [2]. However, these technologies come with challenges and risks, including complex production operations, high production data density, and environmental concerns such as surface ecological damage and pollutant emissions, further impacting shale oil and gas production. To facilitate the upgrading process of China's shale oil and gas industry, this paper presents the current status of Internet of Things (IoT) application technologies for shale oil and gas development and proposes a research outlook based on the concept of green development. Against the backdrop of energy transformation, it offers a reference framework for the sustainable development of China's extensive shale oil and gas resources.